A series of recent high-profile workplace accidents have increased public concern over corporate social responsibility (CSR) practices in the global fashion supply chain. Media and non-government organizations condemn that fashion businesses are pursuing maximum profits while putting worker's health and safety at risk in the production operations. The public condemnation upon occupational health and safety (OHS) issues could hurt consumer's buying intention and consequently the competitiveness of supply chain. Despite most OHS problems often happen in operational settings, current OHS literature lacks an operations management (OM) perspective, with limited implications for operational managers to manage OHS properly so as to achieve sustainable financial performance.This dissertation first provides a Citation Network Analysis review to the current OHS studies in OM literature. This review enables us to identify the research gap on OHS issues in OM. Based on the two popular safety management theories, normal accident theory (NAT) and high-reliability organization theory (HRT), two empirical studies were conducted to examine the relationship between safety and financial performance. The first empirical study reveals the operational antecedent of safety incidents and the practices of OHS management in the operation processes of fashion and textiles manufacturers. Safety incident is an undesirable circumstance that has the potential to cause workplace injuries and illnesses. Results find that tightly coupled operation is a significant predictor of safety incidents (violation of safety regulations), while retaining financial slack resources could reduce the harm of tightly coupled operations. The second empirical study shows that the adoption of OHSAS 18001, a popular occupational health and safety management system certification, could improve firm's safety and financial perfonnance. The firms operating in complex and tightly coupled settings could benefit more from the adoption.This dissertation has essential theoretical contributions to OM and safety research scholars. First, the citation network analysis review identifies five major research domains and backbone knowledge structure of each domain objectively. The future research opportunities of OHS topics in OM literature are proposed. Second, the findings from the two empirical studies syntheses NAT-HRT views on safety and financial perfonnance relationship. The results show that tightly coupled operations would encounter higher safety risk, and the slack resources can be a useful buffer for tightly coupled operations. Third, the finding provides evidence to resolve the productivity-safety paradox and the results suggests that improved safety performance caused by OHSAS 18001 adoption leads to improved financial performance, implying that the merit of safety management is larger than its constriants to the operational efficiency. This dissertation provides several managerial implications to the operations managers in fashion and textiles manufacturers. First, fast fashion manufacturers should be aware that the higher OHS risk in their operation processes results from the tightly coupled operations nature of fast fashion. Second, fast fashion manufacturers should maintain financial slacks to minimize OHS risk. Third, the managers who plan to adopt occupational health and safety management system (i.e., OHSAS 18001 certification) can expect improvement in firm's safety, sales, and productivity performance, especially when the manufacturers are labour and R&amp;D intensive, and the inventory level is volatile.

Global Positioning System(GPS) refelctions is a new technique used in remote sensing applications.Ocean reflection experiment performed in Shen Zhen Xi Chong Astronomical observatory, China equipping with a GNSS-R receiver. Three-day data were collected continuously and rest of the data collected for the dispersion time from November7th to November 11th. Data capture is mainly completed by GPS/BD four-channel GNSS-R IF acquisition developed by Beihang University which can simultaneously capture four GNSS signal with intermediate frequency of 3.996MHz, sample frequency of 16.369 MHz. This dissertation introduces the application in sea surface wind speed montior. The software receiver and algorithms used for Delay Waveforms and Delay-Doppler map genaration and the Delay Waveforms and Delay-Doppler Map selection approches are prensented. The preliminary results of sea surface refelction analysis are also described. Delay of refelcted signal with respect to direct signal is a significant basic for sea level caculation. The refelcted signal correlation power is employed to give qualitative analysis to sea surface wind speed.

In computer vision and pattern recognition, there are a variety of image based classification tasks, e.g., face recognition, action recognition, object recognition, texture classification, handwritten digit recognition, etc. How to choose a suitable classifier for the given classification task is not a trivial problem, and it depends on data type, data distribution, data size, and feature property. According to "no free lunch" theorem in machine learning, there is no one classifier that can always achieve the state-of-the-art performance in all classification tasks. Intuitively, a robust, efficient, and scalable classifier with good understandability, scalability and generalization ability is always desired. Representation based classification has been widely used in pattern classification and achieves superior performance. It is based on the assumption that a query sample can be more accurately approximated by a linear combination of training samples of its class than other classes. Many representation based classification models have been developed, including sparse/collaborative representation, low-rank representation, robust representation, kernel representation, generic representation, multi-modal/cross-modal representation, etc. Representation residuals in these models are discriminative and a query sample can be classified to the class with the minimal reconstruction residual. Meanwhile, representation coefficients can also be used as features to enhance classification. In addition, in middle-level feature extraction, in contrast to vector quantization, sparse coding can be introduced to obtain a soft representation for classification. Although representation based classification models have achieved a great success in different classification tasks, there are still many problems remaining. When there are only a small number of training samples, the representation tends to be over-determined and therefore the query sample may not be well represented. When the number of the training samples is very large, the time complexity and memory consumption of representation based classifiers becomes a challenging issue. Besides, the existing representation based classifiers are mostly designed to accomplish single image based classification tasks. However, for video based face recognition and multi-view object recognition, the task becomes an image set classification problem. It is demanded to extend representation based classifiers from image based to image set based models. Finally, most existing representation based classifiers are non-discriminative in the representation process. It is interesting to investigate if the samples can be projected to a discriminative feature space to enhance the classification performance. In this thesis, we aim to develop new representation based classification models for small sample size problems, big sample size problems, image set classification problems, and discriminative representation problems, respectively. In Chapter 2, to solve the small sample size problem in face recognition, a patch based collaborative representation classifier (PCRC) is proposed. Both the query and gallery face images are divided into patches and then the query patch is represented by the gallery patch dictionary. Classification outputs of all the patches are combined by majority voting to get the final output. As PCRC is sensitive to patch size, a multi-scale PCRC is proposed to fuse the classification outputs of different path sizes by margin distribution optimization.In Chapter 3, a local generic representation (LGR) based approach is proposed for face recognition with single sample per person. A generic intra-class variation dictionary is constructed from a generic dataset, and it can well compensate for the face variations lacked in the gallery set. A correntropy based metric is adopted to measure the loss of each patch so that the importance of different patches in face recognition can be more robustly evaluated. In Chapter 4, a self-representation induced classifier (SRIC) is proposed for representation with big sample size. Different from the existing sample-level representation, we proposed representation based classifiers from the perspective of feature-level representation. The time complexity of SRIC is only related with feature dimension and the number of classes. Hence, it is very suitable for classification tasks with a large amount of training samples and a small number of classes. In Chapter 5, an image set based collaborative representation model is proposed for image set based face recognition. Considering the distinctiveness of samples in the query image set and the correlation between the gallery image sets, we model both the query and gallery image set as hulls. Then the hull of the query image set is collaboratively represented on the gallery image sets. Regularized hull and kernel convex hull are both considered to develop robust image set based collaborative representation classifiers. In Chapter 6, by considering representation based classifiers as point-to-set distance based classifiers, we extended distance metric learning from point-to-point distance to point-to-set and set-to-set distance. The metric learning problem is modeled as a sample pair classification task and can be efficiently solved by standard support vector machine solvers. To sum up, in this thesis we developed patch based collaborative representation, local generic representation, regularized self-representation, image set based collaborative representation, and point-to-set/set-to-set distance metric learning methods to address the representation problems with small sample size, big sample size, and image sets for pattern recognition, respectively. Our extensive experimental results demonstrated the state-of-the-art performance of the proposed methods. In the future work, we will investigate generic dictionary learning for face recognition in the wild, cross-modal/multi-modal dictionary learning and metric learning methods under the representation based pattern classification framework.

Attention is increasing on on-time delivery in the distribution and logistics industry. On-time delivery directly influences customer service levels and is a key delivery service performance measure. Owing to uncertainties in customer demands and travel time variations in urban road networks, on-time deliveries to customers cannot be guaranteed. Travel times in urban road networks are highly stochastic due to roadway capacity variations and traffic demand fluctuations. Customer demands are also varied when a vehicle is on the way to deliver goods to various customer locations. The vehicle capacity may thus be exceeded along a planned delivery route. The vehicle may have to return to the depot to reload. This would lead to additional travel times or delays for delivery. The vehicle routing problem (VRP) involves planning a set of minimum-cost delivery routes for the vehicles of a distribution company to serve a group of geographically scattered customers. It has broad applications in distribution and logistics management fields and has been extensively studied over the past decades. One important variant of the VRP is called the VRP with time windows. In this problem, each customer may require to be served within a given time interval (i.e. time window). Due to uncertainties in customer demands and travel time variations in urban road networks as stated above, on-time deliveries to these customers cannot be ensured. This is a critical issue in practical scenarios. However, little attention has been paid to specifically address the on-time delivery issue under uncertainties in travel times and/or customer demands. In view of the above, this thesis investigates the on-time delivery issue in two stochastic VRPs: the VRP with stochastic travel times and time windows (VRPSTT-TW) and the VRP with stochastic demands and time windows (VRPSD-TW). The thesis contributes to the literature of stochastic VRPs in the following aspects.Firstly, a new stochastic programming model is proposed for the VRPSTT-TW (and is later extended for the VRPSD-TW) that explicitly addresses the on-time delivery issue under uncertainties in travel times. This model is formulated from the point view of an operator who wishes to reduce the total expected cost of delivery (and particularly to reduce the cost of deploying the required vehicles), but at the same time would like to achieve certain service level requirements in terms of on-time deliveries to customers. More specifically, the proposed model embeds probabilistic customer service level constraints within a traditional stochastic programming with recourse model. The proposed model can be used to design a set of delivery routes that minimizes the total expected cost of delivery (including the cost of deploying the required vehicles), while ensuring a given on-time delivery probability to each customer. Secondly, an iterated tabu search heuristic algorithm is developed to solve the proposed model for the VRPSTT-TW. To minimize the number of vehicles required, a route reduction mechanism is designed and incorporated in the developed heuristic algorithm. A discrete approximation method is also presented for estimating the distribution of the vehicle arrival time at each customer location in the presence of time windows. Using this approximation method, solutions to the proposed model can be evaluated without suffering restrictions on the assumption of travel time distributions. Thirdly, a new probabilistic model is proposed for the VRPSD-TW that addresses the on-time delivery issue under uncertainties in customer demands from the customer perspective. This model seeks to plan a set of delivery routes that maximizes the sum of on-time delivery probabilities to all the customers, provided that the maximum number of vehicles for delivery of goods is given and fixed. The proposed model attempts to answer the question of &quot;what is the best possible on-time delivery performance of a distribution company with a fixed-size fleet of vehicles for delivery of goods?&quot; Fourthly, the applicability of a preventive restocking (PR) policy is examined for the models proposed for the VRPSD-TW. Under a traditional detour-to-depot (DTD) recourse policy, a vehicle would return to the depot to reload only when the remaining vehicle capacity becomes zero or is exceeded along a planned delivery route. Under the PR policy, the vehicle would return to the depot to reload if the remaining vehicle capacity is below a predetermined level. In this thesis, it is shown that the PR policy can help to generate delivery solutions better than those resulting from the traditional DTD recourse policy.

This thesis is concerned with modelling the processes of meaning making. The central goal is to explore the expansion of meaning potential constructed by both linguistic resources and visual images in English Language Teaching (ELT) textbooks used in Hong Kong primary and secondary schools. The exploration is based on systemic-functional theory and draws on insights from educational linguistics. Through empirical analysis of all the verbal texts and visual images included in thirteen ELT textbooks, this thesis explicates the ontogenetic expansion of the meaning potential as it is progressively constructed in successive textbooks. Chapter 1 provides an overview of the theoretical and contextual backgrounds. Motivated by functional linguistic approaches to language development this thesis adopts an ontogenetic perspective to investigate textbooks as language learning materials during schooling, aiming to provide a systematic modelling of meaning construction in textbooks. The contextual motivation of this thesis stems from the recent academic reform in Hong Kong. As a consequence of this reform, the Education Bureau now stresses that students experience a smooth transition as they progress from grade to grade. Whether the current English textbooks support or impede the smooth transition is addressed in this study. Chapters 2 to 4 set out the foundations of the current study. Chapter 2 reviews relevant issues on textbooks studies. In particular, the historical development of textbook design underlying the historical development of language teaching approaches is introduced. Chapter 2 also reviews the previous studies on textbook analysis. Chapter 3 outlines different approaches to explore the ontogenetic expansion of the meaning potentials of learners, especially the functional linguistic approaches underpinning the current thesis. In Chapter 4, I elucidate the main theoretical foundations of the thesis, which include the systemic functional model of language and the stratified relations between context, discourse and language. Chapters 5 to 7 present the main theoretical frameworks and analyses of verbal texts and visual images extracted from the textbooks. Chapter 5 introduces the contextual background and the research design. In Chapter 6, I investigate the expansion of meaning potential as constructed by verbal texts in the textbooks. Chapter 7 presents the meaning construction of visual images. Chapter 8 further extends this thesis from learning materials for primary and secondary levels to include learning materials for the tertiary level by outlining a pilot study on college textbooks. In Chapter 9 I conclude by summarizing the major findings of the research and its contribution to both language education and the exploration of meaning construction. Chapter 9 also discusses the limitations of the current study and the possible directions of further study. The research is significant in both the theoretical and practical spheres: on the one hand, it serves as the starting point for future studies exploring multilingual meaning potential from an ontogenetic perspective, and on the other hand it maps out the systematic modelling of meaning potential constructed in language learning materials during schooling, providing insights for curriculum development and material design in English as a second or foreign language (ESL/EFL) context.

Compared to chilled water-based large-scale central air conditioning (AlC) systems, direct expansion (DX) A/C systems are simpler in configuration, more energy efficient and generally cost less to own and maintain. Therefore, for the last few decades, DX A/C systems have found increasingly applications in buildings, particularly in small to medium-scale buildings. However, currently most DX A/C systems are equipped with single-speed compressors and fans, relying on on-off cycling to maintain indoor dry-bulb temperatures only. This results in an uncontrolled equilibrium indoor humidity and possible space over-cooling if indoor humidity level is to be maintained at an acceptable level. These will lead to a reduced level of thermal comfort for occupants, poor indoor air quality (IAQ) and low energy efficiency. The development of variable-speed (VS) technology has made the continuous control of compressor speed and supply fan speed in a DX A/C system more practical, paving the way for achieving simultaneous control of indoor air temperature and relative humidity using DX A/C systems. For a VS DX A/C system, varying its compressor speed and supply fan speed influences on its output sensible and latent cooling capacities, which is part of the operational characteristics of the VS DX A/C system. Previous extensive experimental studies demonstrated that inlet indoor air temperature and humidity would, however, have also influence on the operational characteristics of a VS DX A/C system, with the extent of influences to be further studied. On the other hand, different attempts have been made to develop control strategies for the simultaneous control of indoor air temperature and humidity using a VS DX A/C system. Each controller developed has however its inadequacy because of both the difficulties of accurately modeling the complex heat and mass transfer between the refrigerant and air in a DX evaporator, and the coupling effects for the control loops for air temperature and humidity. Recently, artificial intelligent control strategies have been widely applied to building heating, ventilation and air conditioning (HVAC) systems. Among various artificial intelligent control strategies, fuzzy logic (FL) is promising for achieving improved control of HVAC systems, because FL is very useful when the processes under consideration are too complex to be analyzed by conventional quantitative techniques or when the available sources of information are interpreted qualitatively, inexactly or uncertainly. Furthermore, artificial neural network (ANN) has been proven to be powerful in modeling the dynamic performance of a nonlinear multivariable system without requiring a physical model. Therefore, the application of fuzzy logic or ANN, individually or jointly, helps address the issue of simultaneously controlling indoor air temperature and humidity using a VS DX A/C system. Therefore, in this Thesis, a study to further investigate the operational characteristics of a VS DX A/C system at different inlet air states, and to develop novel controllers that can simultaneously control indoor air temperature and humidity using a VS DX A/C system following fuzzy logic and ANN approaches is reported. The Thesis, first of all, begins with presenting an experimental study on the operational characteristics of a VS DX A/C system at six different inlet air states to the system, which is a follow-up investigation to a previous related experimental study but at only two inlet air states. The study results suggested that different inlet air states to a DX A/C system influenced the operational characteristic of the system, in terms of the Inherent Correlations (IC) between its output total cooling capacity (TCC) and equipment sensible heat ratio (E SHR). Therefore, a further data processing method was developed using regression, by which the ICs of the VS DX A/C system at non-test inlet air states can be predicted with adequate accuracy. This study has therefore, on one hand, provided a further detailed understanding of the operational characteristics of the DX A/C system, and on the other hand, paved way to developing advanced control strategies for indoor thermal environment (i.e., air temperature and humidity) based on the known or predicted ICs within the possible operating ranges of inlet air temperature and humidity to the DX A/C system.Secondly, this Thesis reports on the developments of two novel controllers as two different approaches to solve the same problem of simultaneously controlling indoor air temperature and humidity using a VS DX A/C system. For the first one, based on the obtained ICs of the VS DX A/C system, a novel ANN aided fuzzy logic controller, which combined the complementary merits of fuzzy logic controller and ANN modeling, was developed and experimentally validated. A novel control principle was proposed to decouple the temperature and humidity control loops by introducing two interim variables of sensible output cooling capacity and latent output cooling capacity of the VS DX A/C system. A fuzzy logic system was redesigned to simplify both its calculation and structure by using weights assigned to linguistic variables. To enable ANN models developed to be functional over the normal operational range of indoor air parameters, the obtained ICs of the VS DX A/C system were used for training and testing the ANN models. The novel controller developed was tested using the experimental VS DX A/C system. Both the command following tests and disturbance rejection tests showed that air dry-bulb and wet-bulb temperatures were properly controlled by the controller developed with satisfactory control performances in terms of control accuracy and sensitivity. However, on the other hand, the other controller developed was a novel PD-law based fuzzy logic controller (PFC). To weaken the coupling effect between two control loops, fuzzy logic was deployed. A PD law was used instead of a PID law in the PFC, which could help simplify not only calculation but also the structure of the PFC. The controller developed was also validated by carrying out the controllability tests, including the command following test, disturbance rejection test and the command following with disturbance test, with the experimental conditions covering the normal operational range of a VS DX A/C system. The experimental results of the controllability tests suggested that the novel PFC developed was also capable of realizing the simultaneous control of indoor air temperature and humidity satisfactorily, in terms of control accuracy and sensitivity. Thirdly, this Thesis presents the performance comparisons between the two developed novel controllers, using that of an ON / OFF controller as a benchmark for the VS DX A/C system, in terms of control performance and energy efficiency. Comparison experiments for the three controllers were carried out under different operating conditions using the VS DX A/C system. Both the merits and shortcomings of the developed novel controllers are reported. With this study reported in this Thesis, a better understanding of operational characteristics of a VS DX A/C system has been obtained. Furthermore, novel controllers based on fuzzy logic and ANN have been developed to address the simultaneous control of indoor air temperature and humidity using a VS DX A/C system. The outputs from this study can help improve occupants' thermal comfort level and indoor air quality and enhance the energy efficiency of VS DX A/C systems.

Anaerobic digestion is a bio-chemical process that is commonly used to concert macromolecule organic compounds (wastes) into a useful biogas with methane as the energy carriers. Increasingly, AD is being applied in industrial, agricultural, and municipal waste (water) treatment facilities. The use of AD technology allows plant operation to reduce waste disposal costs and offset energy utility expenses. In addition to treating organic wastes, energy crops are being transferred into methane as the energy carrier. As the application of AD technology broadens for the treatment of new substrates and co-substrate mixtures, so does the demand for a reliable testing methodology at the pilot-and laboratory-scale. Continuous Stirring Tank Reactor (CSTR), as one of the common configurations of anaerobic digestion systems, is frequently applied in research due to simplicity of design, operation and maintenance itself, and its advantages for experimentation as well. CSTR would provide as much system parameters as temperature, mixing, chemical components, and substrate concentration comparing to other prototypes. Therefore, we designed and constructed two exact same CSTRs for disposing two different types of sewage sludge for most preliminary analysis. Despite of daily preliminary assessments, it is worth noting that the sewage sludge as substrates coming from two different sewage treatment plants, ST sludge contains high concentration of sulfur, and we would like to study the changing of H₂S/SO₄²⁻ in our CSTR system for the reason that sulfur and sulfate would certainly cause impacts to anaerobic digestion system.

This thesis presents the investigations on the optimal design and control of cool thermal storage systems for building demand management. The developed strategies include optimal design of active cool thermal energy storage (CTES) for building peak load management, fast power demand response (DR) strategies for buildings involving both active and passive CTES for smart grid applications and optimal design of active CTES for building demand management. These new strategies in different subjects are proposed and validated on a dynamic simulation platform. A simulation-based optimal design method is developed and used to optimize the capacity of CTES. The quantitative analysis on the life-cycle cost saving potentials of active cold storage systems concerning the operational cost, initial investment and the space cost is also proposed. The optimal capacities of active CTES, monthly/annual operational cost savings and corresponding peak demand set-points are obtained from using the marginal decision rule. Results show that small scale storages can offer substantial annual net cost saving. Two fast power DR strategies involving both active and passive cool storages are presented. Certain number of operating chiller(s) is shut down at the beginning of the DR event to achieve a significant and immediate power reduction. In the basic fast DR strategy, only chiller power demand reduction is the control objective while in the improved fast power DR strategy, the building indoor temperature during the DR event is the second control objective to control indoor thermal comfort degradation. The results of case studies show that stepped and significant power reduction can be achieved. The power demand reduction and indoor temperature during the DR event can be also predicted accurately. The life-cycle cost benefit analysis and optimal design of active CTES for building demand management is also proposed. It is assumed that the active CTES is under control of the fast power DR strategy during the DR event. Meanwhile, during the normal days, the active CTES is under control of the storage-priority control to shift peak demand. Based on the different indoor thermal comfort requirements, the optimized capacities of active CTES, the corresponding life-cycle cost saving potentials and the chiller power reduction set-points in the developed fast power DR strategy are then identified. The results show that the optimal capacity of active CTES largely increases with the decrease of the upper limit of indoor temperature set-point.

This dissertation aims to optimize the operation performance of a sewage pumping station in Hong Kong. The solutions of two main problems occurred in the operation of the Harbour Area Treatment Scheme have been investigated, i.e. the sewage overflow and high energy consumption for running the pumps.The Harbour Area Treatment Scheme ("HATS") is a major governmental initiative to improve the water quality in Victoria Harbour, which provides proper collection, treatment and disposal of all wastewater discharged into the Harbour from the urban areas of Kowloon and Hong Kong Island. In this dissertation, the background of the HATS is introduced and the relevant literatures are reviewed at first. It was found that the main problem of this system is that sewage overflow sometimes is out of control when different factors appear, such as unexpected rainfall and behaviors of human beings. In this study, the model of a neural network, especially for BP networks, was applied to forecast the operation performance of the sewage overflow. What is more, the problem of high energy consumption of pumps was also discussed for a solution. In this essay, to boost the operation performance, the target rotational speed was detached on the basis of formulas. Finally, by comparisons, the optimized simulation results and actual operation data were, found and a method is thus proposed.

Optofluidics is a new technology that enables simultaneous delivery of light and fluids with microscopic precision. This study aims to explore the opportunities of applying the optofluidics technology to the photocatalytic systems for water purification. In this study, three types of optofluidic reactors for photocatalysis water purification are designed, fabricated and characterized to overcome the fundamental limitations of current bulk reactors. The first design is a planar reactor that attempts to overcome the mass transfer limit and the photon transfer limit in the bulk reactors. It has exhibited promising features such as small sample volume, short reaction time and easy flow control. The degradation percentage reaches 94% at the effective residence time of 36 s and the degradation rate gets up to 8%/s at the effective residence time of 6 s. Its success has encouraged the proposal of the second design, which uses BiVO4 as the visible photocatalyst and mounts a blue-light LED panel as the integrated light source. The mounted LED provides uniform irradiation of light and enables to utilize the heat of light source to assist the photodegradation. The degradation efficiency was increased by 4 times and the heat contribution to degradation was about 4~6%. The third design is a novel photoelectrocatalytic microreactor, which aims to eliminate a fundamental limit of photocatalysis the recombination of photo-excited electrons and holes by applying an external electric field. In the experiment, positive and negative bias potentials are applied across the reaction chamber to suppress the e-/h+ recombination and to select either the hole-driven or electron-driven oxidation pathway. Another important feature is that the degradation percentage increases linearly with the residence time. It is 5.2% s⁻¹ for the negative bias state and 4.7% s⁻¹ for the positive bias state. In summary, the optofluidic microreactors have been developed to help overcome different problems in the bulk reactors such as photon transfer limitation, mass transfer limitation, oxygen deficiency, and lack of reaction pathway control. These reactors may find niche applications in rapid screening and standardized tests of photocatalysts and may also be scaled up for large-throughput industrial applications of water process.

Fabric and clothing products with functional surface finishing treatments can achieve better end use properties. Functional textiles considerably improve the performance in a wide variety of applications and meet consumers' demands of comfortable and health care as well as protection against chemical,mechanical, thermal and biological attacks. The functionalization of textiles was well developed in the past decade, but there are still many disadvantages or challenges, for example, some of them have harmful effects to human and cause pollution to the environment. New technologies in material science need to be applied to the traditional textile industry to develop and produce high value added products and overcome the problems associated with the conventional finishing treatments. This research presents new and innovative approaches to functionalize textile materials based on organosilicon compounds via in situ sol-gel technology. The approaches developed here are to form micro-nanocomposite assemblies directly on fiber surfaces and impart multifunction to textile substrates in an environmentally friendly way. Up to now, water repellent function continues to take a large share in the functional fabrics market and is gaining universal acceptance. For this purpose, fluorocarbons with low surface energy are the important repellent agents and are widely used for textile finishing. But, the fluorine chemicals are mainly based on perfluorooctanoic acid (PFOA) derivatives. There are some evidences concerning possible persistence, bioaccumulation, and/or toxicity of these types of fluorocarbon chemicals in the environment, which make them less and less desirable in industrial applications. In this project, a non-fluorinated water-based hybrid organosilicon miniemulsion was prepared by using methyl trimethoxy silane (MTMS), 3-glycidyloxypropyl trimethoxysilane (GPTMS) and hexadecyltrimethoxysilane (HDTMS) under ultrasonication and a very small amount of surfactant. The as-prepared miniemulsion was applied on cotton fabrics by a conventional pad-dry-cure process. After padding, the wet fabrics were fumigated under ammonia atmosphere for in situ condensation of siloxanes on cotton fiber surfaces. The treated cotton fabrics have an artificial lotus leaf roughness structure and exhibit excellent water repellent property with 153.7° water contact angle and 100 in water spray rating, the water repellency can also afford 30 home launderings.Secondly, for some synthetic fibrous textiles, especially those after water repellent treatment, high specific resistance and low moisture regain lead to the static problem. The static electrical charges do not easily dissipated and result in the attraction to dust, electric shocks and even fire hazards. Anti-static treatment therefore becomes necessary. Most antistatic agents can decrease static charge accumulations because of its hydrophilic property by absorbing water from the air. But, these moisture-absorbing coatings will undermine the hydrophobic property. This project succeeds in combining carbon nanotubes (CNTs) with hydrophobic HDTMS to achieve both water repellent and antistatic properties for polyester fabrics via in situ sol-gel method. CNTs in this system act as not only antistatic agent but also micro-rough structure building agent.What's more, the mechanism of CNTs as an antistatic agent does not have adverse effect on the water-repellent property. The treated polyester fabric with "micro-wrinkle" structure shows excellent water repellency and antistatic properties, as well as good wash fastness.Thirdly, this project also presents the preparation of a formaldehyde-free and halogen-free UV-blocking and flame-retardant hybrid coating for cotton fabric via in situ sol-gel method. Cotton as the most important natural fiber is widely used as clothing material, but very ease to thermal degradation, ignition and burning. Flame-retardant (FR) treatment of cotton is very important for preventing fire and protecting human life. However, the most efficient and widely used halogen-based FR compounds can produce a large amount of smoke and toxic gases during the combustion process. Some of them were even banned by USA and EU. Some phosphorous-based compounds including N-methylol dimethylphosphono propionamide (MDPA) and tetrakis hydroxymethyl phosphonium chloride (THPC) and are widely used as halogen-free FRs.However, these types of FRs also have the disadvantage of formaldehyde release. Formaldehyde is a well-known carcinogen compound confirmed by the World Health Organization.In this project, a hybrid sol was prepared based on tetraethylorthosilicate (TEOS), GPTMS and Mg(CH₃COO)₂. The as-prepared hybrid sol was used for cotton fabric treatment by a conventional dip-pad-cure process. The padded cotton fabric was also put into ammonia atmosphere for in-situ deposition and condensation of Mg(OH)₂/silicon assemblies on cotton fibers. The vertical flammability and ultraviolet protection factor (UPF) testing results showed that this uniform Mg(OH)₂/silicon composite coating acting as a physical barrier can achieve excellent flame-retardant and UV-blocking properties. The research works presented in this thesis are focused on an organosilicon-based in situ sol-gel technology to treat textile materials with multifunctions. The nano-microcomposite coatings were directly in situ prepared on fiber surfaces for multifunctions, synergistism and durability. The chemical systems prepared in this project can bring high performance and added value to the textile products, while at the same time have minimal impact to the environment. The methods developed in this project can also provide generic approaches for textile chemists in functionalization of textiles or other flexible substrates, and are of highly potential for industrial mass production.

Outdoor thermal comfort has become a public concern relevant to human health. The outdoor spaces in Hong Kong, which is a sub-tropical city, is less used due to thermal discomfort. Thermal sensation is not only affected by microclimate but also thermal adaptation, which involves physiological, psychological and behavior factors. In order to make outdoor spaces more comfortable to pedestrian and to make outdoor environment pleasant for people to use and enjoy, better understanding of the thermal sensation of people is needed. This paper presents the field measurements and questionnaire survey results of an outdoor thermal comfort study conducted in Hong Kong Polytechnic University, which reveals wind speed, relative humidity, air temperature and globe temperature. The physical measurement was dealt with based on PMV (Fanger), PET and SET* using a software called RayMan. The results of questionnaire survey were correlated with the micro-meteorological data to analyze the general outdoor thermal comfort conditions on campus. The results showed that outdoor thermal comfort varies due to the wind modification and shading effects including the position and distribution of building blocks. Some suggestions were achieved by a better understanding towards constructions affecting human thermal perception in Hong Kong. This understanding makes a contribution towards building designers and planners for creating a more thermally comfortable outdoor space in hot and humid tropical and sub-tropical cities.

I analyze the relationship between the overlap of board members and the CEOs compensation. If the members of audit committee and compensation committee are overlapped, then the directors who sit in both committees will worry about the costs and efforts they have to pay to monitor the financial reporting process. Such concern will make them lower the pay-performance sensitivities of the CEOs compensation. Conversely, if the tasks of setting compensation and monitoring financial reporting process are assigned to different people, the pay-performance sensitivity will be higher. Increased compensation pay will become motivation for the CEOs to engage in earnings management, putting the directors in audit committee under greater pressure to diligently perform the monitoring work. I find that the pay-performance sensitivities of the CEOs compensation decrease with the overlap of directors in the audit committee and compensation committee. Besides, I also find that the audit fees increase with the separation of directors in the two committees.

This study contributes to the institutional theory of corporate governance literature by identifying the relationship between earnings quality and ownership concentration. Using data and published information taken from listed firms in Hong Kong, it determines whether such a relationship is moderated by various audit committee characteristics, including independence, the financial expertise of audit committee members, gender diversity, and audit activity. It also considers how this relationship differs in extreme economic environments, as was the case during the financial crisis in 2008. One hundred and fifty-four firms listed on the Hong Kong Stock Exchange in 2008 were randomly selected to test the hypothesis that firms with a high ownership concentration exhibit higher earnings quality. A similar test was run for the same list of firms using data and published information from 2011. The results provide evidence that ownership concentration has a positive relationship with earnings quality (and alternatively a negative relationship with earnings management). This study also examines the relationship between each of the aforementioned four audit committee characteristics and earnings quality. There is no evidence that audit committee characteristics and earnings quality have any significant relationship, confirming that the research in this area yields mixed results.Based on the test results, this study suggests that corporate governance in Hong Kong follows the institutional strand,indicating that audit committees and outside directors serve a ritualistic function rather than a monitoring role. Finally, the two variables ownership concentration and audit committees, are interacted, and no evidence is found to support the notion that audit committees play a significant role in constraining earnings management behavior. However, the characteristic of financial expertise does have a moderating effect on the relationship between ownership concentration and earnings quality for firms operating in the financially turbulent year of 2008.Consistent with the literature that finds that outside directors are appointed to boards to provide strategic advice rather than to monitor managerial activity, especially when they are in possession of specialized knowledge such as financial expertise, this study concludes that under extreme financial conditions such as financial crises, audit committees play a more proactive role in terms of constraining opportunistic behavior such as earnings management behavior. Audit committee members who possess specialized financial knowledge and expertise are also consulted more extensively during financial crises by family firms seeking to improve their earnings quality in general.

Palladium-catalyzed ortho-selective arene CH functionalizations are promising approach for developing sustainable organic synthesis. Most successful examples involve alkenes/alkynes and organometallic reagents for CC bond formation. This thesis explores the catalytic coupling of arenes with aldehydes and chloroform for regioselective CC bond formation. Our study showed the principal step involves transforming the aldehydes and chloroform to carboradicals, which are key intermediates for the coupling reactions. To begin, direct acylation of acetophenones with aldehydes to afford 1,2-diacylbenzenes was examined. Treating acetophenone O-methyloxime with 4-chlorobenzaldehyde (2a), TBHP and Pd(OAc)₂ (5 mol%) in toluene at 100 °C furnished the desired benzophenone (3a) in 71% yield. This acylation reaction exhibits excellent ortho-selectivity; functional groups such as methoxy, sulfonyl, halogen and amide were tolerated. Apart from benzaldehyde, aliphatic and heteroaromatic aldehydes are also effective partners with 55-95% product yields being achieved. In this work, 3a was deoximinated to give diketone (4a) which was converted to phthalazines - a medicinally useful heterocycle. The related ortho-selective acylation of anilides was examined for synthesis of 2-aminobenzophenones. Treating N-pivalanilides (6a) with 4-chlorobenzaldehyde, TBHP, TFA (1 equiv) and Pd(OAc)₂ (5 mol%) in toluene at 40 °C for 3 h, produced the corresponding ortho-acylated anilide in 80% yield. This anilide acylation also displayed excellent ortho-selectivity and functional group tolerance for a wide range of substrates. For example, aldehydes containing heteroaromatic rings and strained cyclopropanes have been successfully coupled to anilides.Kinetic study on the acylation of 2-phenylpyridine (8a) with 4-chlorobenzaldehyde (2a) with TBHP revealed an experimental rate law : rate = k[8a]-1[Pd]². The inverse first-order dependence of [8a] suggests that the turnover-limiting step should involve substrate dissociation. The second-order dependence on [Pd] suggests the involvement of dinuclear palladium complex in the turnover-limiting step. With 8a-d5 as substrate, significant primary kinetic isotope effect (kH / kD = 5.6) is consistent with substantial CH bond cleavage at the turnover-limiting step. A Hammett correlation study on a series of meta-substituted pivalanilides (6) (Y = OMe, Me, Ph, H, Cl and Br) revealed a linear free energy relationship (R = 0.96) and small ρ⁺ value of -0.74. The small negative ρ⁺ value implies that the Pd(II)-mediated CH cleavage should not proceed through an cationic arene intermediate. Reacting the cyclopalladated complex [Pd(C~N)(OAc)]₂ (C~N = 2-phenylpyridine) (8a-Pd) with 2a (3 equiv) and TBHP (2 equiv) afforded the coupled ketone in 42% yield. The catalytic CH acylation was suppressed by radical scavengers such as ascorbic acid in a dose-dependent manner. When 2,2,6,6-tetramethylpiperidine N-oxide (TEMPO) (1 equiv) was employed as additives, the ketones formation was completely suppressed and the 2,2,6,6-tetramethylpiperidino-4-chlorobenzoate was isolated in 78% yield. These finding are compatible to intermediacy of carboradicals in the acylation reaction. The catalytic acylation is probably mediated by coupling of the carboradicals with the arylpalladium(II) complexes. Trichloromethyl moiety is prevalent to many medicinally useful molecules such as dysamide, barbamide and muironolide. In this work, we examined trichloromethyl [CCl3] radical generated from chloroform for CH coupling reactions. Treating cyclopalladated complex 8a-Pd with di-tert-butylperoxide in chloroform at 120 °C failed to afford any trichloromethylated arenes. However, treating N-arylacrylamides (1 equiv) with di-tert-butylperoxide in chloroform in 120 °C furnished the carbocyclized 2-oxindoles (10a) in 68% yield. In the presence of CuBr₂ (5 mol%), this reaction proceeded to give the 2-oxindole up to 87% yield. Functional groups such as methoxy, halogen and ketone groups are well tolerated.

Data mining tasks such as clustering, outlier detection and similarity search typically employ a series of algorithms to operate on a large set of data, making them amenable to parallelization. Thus parallelization of data mining operations such as distance computation has been extensively studied in the literature. In recent years, the use of Graphics Processing Units (GPUs) for data mining has been steadily increasing. As state-of-the-art processors now include both CPU and GPU, it is important to consider which approaches benefit from GPU processing and which do not, and apply a heterogeneous processing approach to improve the efficiency when applicable. Similarity search, also referred to as k-nearest neighbor search, is a particular application of distance computation where only to top k results (e.g., top 10) are required. It is used extensively in multimedia search, where only a small subset of possible results are used, and numerous approaches using both exact and approximate k-nearest neighbor methods have been proposed over the years. Our contribution is a new exact distance algorithm that not only outperforms competing exact GPU methods, but can compete with leading approximate GPU methods. It can also leverage heterogeneous (CPU-GPU) processing for improved efficiency. Outlier detection, also known as anomaly detection, involves detecting data points that deviate from expected patterns. It is an important part of applications such as fraud detection and system fault detection. In many real-world applications such as wireless sensor readings and weather forecasts, data are uncertain in nature. Rather than discarding uncertainty information or storing many sample readings, it is possible to instead approximate the probability distribution function (pdf) to compactly store and efficiently calculate uncertain distance when required. Existing GPU approaches are limited to working with certain data, while our contribution is a parallel method for outlier detection on uncertain data. Clustering is another common operation in data mining. Our work focuses on a particular application, label generation for web search results that automatically generates labels for related topics returned by a user's web search. This is accomplished using a fuzzy transduction-based relational model. We also contribute a GPU implementation of our proposed solution.

The Volterra series based nonlinear analysis and design methodology is a powerful tool that has been applied to various engineering practices. This study addresses several key issues of the Volterra series based methodology that have not been well developed in the literature, including its convergence, applications, and extensions. Two novel concepts, i.e., the parametric bound of convergence (PBoC) and parametric convergence margin (PCM), are proposed for nonlinear systems described by nonlinear auto-regressive with exogenous input (NARX) models. The proposed PBoC can calculate the convergence bound not only for the input magnitude, but also for the parameters of interest. The PCM is developed as a quantitative assessment to examine the distance from a given nonlinear system to the bound of a convergent Volterra series expansion. By applying the theoretical results above, the nonlinear characteristic output spectrum (nCOS) function can be well analysed and designed within a certain region of nonlinear parameters of interest. A nonlinear damping is proposed to overcome the well-known dilemma with respect to linear damping. The performance of the nonlinear damping is derived with the nCOS method, which also provides a straightforward and effective way to tackle the multiple-object nonlinear optimization problem. Linear components or linear controllers are usually easier to implement in practice, and are thus of considerable interest for analysis and design to achieve a better performance when simultaneously considering a system that is inherently nonlinear. The existing nCOS method is only available for nonlinear parameters, and thus is extended to those linear parameters of interest. A symbolic algorithm for calculating the new nCOS function is developed for single-input single-output (SISO) systems. In case that the built symbolic algorithm is complicated for MIMO systems, a numerical identification method is developed. The results above are established for nonlinear systems with polynomial nonlinearity. For those nonlinear systems with exponential-type nonlinearity, there would be too many parameters in the analysis and design because exponential nonlinearity is usually approximated by Taylor series expansions. An efficient algorithm with many fewer parameters for calculating the generalized frequency response function (GFRF) in the nonlinear analysis and design is then developed. The contributions of this thesis lie in the following points. The results of PBoC and PCM are notable extensions of those convergence results in the literature, and can provide a more straightforward and useful guidance for the parameter design or feedback design of nonlinear systems via the nCOS method. The new nCOS function can provide a straightforward understanding of the effect of the linear parameters of interest on the nonlinear output spectrum and thereby greatly facilitate the analysis and design of linear components or controllers for nonlinear systems. The extension of the nCOS method to exponential-type nonlinear system will considerably ease the analysis and design of systems with exponential nonlinearity, such as amplifier circuits and neural networks, in the frequency domain.

Serum 25-hydroxyvitamin D is considered to be the best indicator of overall vitamin D status of an individual. People with vitamin D deficiency will suffer from malabsorption of calcium, secondary hyperparathyroidism, leading to increased bone resorption, accelerated cortical bone loss, and increased fractures. Severe vitamin D deficiency can also cause osteomalacia. Vitamin D status is related to serum PTH. But there is still debate how far the serum vitamin D concentration has to fall to impact significantly on increasing plasma PTH levels, and at what ‘threshold’ level of vitamin D there is no further decrease in PTH a level that could indicate sufficiency, at least in terms of bone health. Objective: (A) Examine the correlation and relationship between plasma PTH and vitamin D status (assessed by plasma 25OHD) in a group of apparently healthy young Chinese adults (N=80, Aged 18-24) in order to seek evidence of a threshold or plateau at which changes in one parameter cease to influence the other; (B) To explore the relationships between PTH, vitamin D, phosphate and calcium in plasma. Design and Participants: This was a cross-sectional analysis. A total of 80 heparinized plasma samples were collected for PTH, calcium and phosphate test. The samples had been collected over around 18 months in 2013-14 from 80 apparently healthy young Chinese students of the Hong Kong Polytechnic University with their informed consent. Results: The mean of 25 (OH)D in this study is 44.92 nmol/L. In this study, the threshold for vitamin D sufficiency was set at the 50 nmol/L cutoff for plasma 25(OH)D. The plasma PTH was inversely correlated with plasma 25OHD (r= -0.313, p=0.005). A significant inverse association between PTH and calcium (r= -0.525 p<.001) was observed, while PTH was directly, though weakly, correlated to phosphate (r=0.26, p= 0.02). No threshold value of vitamin D insufficiency was found. However, the threshold 25 (OH)D value (in relation to effects on PTH) may be within the range of 45-51 nmol/L. Conclusion: Vitamin D insufficiency is common among young Hong Kong people.

Advancements in science and digital technologies have fundamentally changed the world of textiles and clothing. The new global fashion industry is demanding that graduates possess new knowledge, skills and ability in apparel product design. The existing curriculum must change to teach students digital technology and computational design. This thesis reports a study of an integrated e-learning strategy to help students with clothing thermal functional design (CTFD). To achieve the aims of the study the following research objectives were identified and achieved: development of a pedagogical framework for the integrated e-learning strategy for students' acquisition of requisite knowledge, skills and application ability in CTFD, identification of the pedagogical effects of the e-learning technologies on students' learning cycles, learning environment and learning outcomes in CTFD; development of a pedagogical model for teaching computational design in CTFD; and identification of a pedagogical comparison between the integrated e-learning and traditional strategies for teaching CTFD.A pedagogical framework was developed on the basis of Kolb's Experiential Learning Theory with the utilization of virtual laboratories, learning with computer simulations and project-based learning. According to the framework, students experience three approaches: a virtual laboratory, computer simulations, and a project. The framework consists of three elements: objective-oriented (knowledge, skills, and application), behavior-oriented (exploration, simulation, and creation), and cognition-oriented (conceptual, procedural, and integrative understanding).The pedagogical effects of three e-learning technologies on students' learning cycles, learning environment and learning outcomes in CTFD were investigated. First, the virtual wear trial laboratory (VWT-Lab) was employed to teach 38 students in two subjects. The VWT-Lab played as the first-staged learning of "Concrete Experience (CE)" and "Reflective Observation (RO)" in the whole cycle of the integrated e-learning for CTFD and provided a "conceptual scaffolding" learning environment for the students. Pre-post test results showed statistically significant improvement in students' learning outcomes on knowledge components of CTFD. In addition, the results of a feedback survey showed that the students enjoyed learning using the virtual wear trial laboratory. Second, the computational design simulations (CD-Sims) were employed to teach 48 students in two subjects. The CD-Sims played as the second-staged learning of "Abstract Conceptualization (AC)" in the whole learning cycle and provided a "procedural scaffolding" learning environment. Pre-post test results showed statistically significant improvement in students’ learning outcomes on the skills components of CTFD. In addition, the results of students' self-reflections indicated that they thought the CD-Sims were the most important and unique skills learned in the subject, which helped them in understanding the fabric properties, estimating and predicting the functional performance of the design by considering more factors, and having competitive advantages for their future careers. Third, the computational design project (CD-Project) was employed to teach 48 students (12 project groups) in two subjects. The CD-Project played as the third-staged learning of "Active Experimentation (AE)" in the whole learning cycle and provided a "metacognitive scaffolding" learning environment. Pre-post test results showed statistically significant improvement in the students' learning outcomes on application components of CTFD. In addition, students reported in their self-reflections that they could apply the knowledge and skills learned from the CD-Project experience in their career development.The pedagogical model called CPI (Conceptual-Procedural-Integrative) learning was developed for teaching computational design in CTFD. The aim of the CPI learning model was to help students' learning of staged objectives (knowledge, skills, and application) of computational design in CTFD. Based on three technologies (virtual environment, computer simulation, and computer-aided design), three staged pedagogical approaches (virtual wear trial learning, 3M learning, and F/P-oriented design learning) individually employ three staged instruments (VWT-Lab, CD-Sims, and CD-Project) for students' (conceptual, procedural, and integrative) learning through staged experience (exploration, simulation, and creation) and cognitive process (connective thinking, critical thinking, and creative thinking). Pre-post test results from a whole-semester subject showed statistically significant improvement in the students' learning outcomes on knowledge, skills and application components of CTFD after using the (CPI learning pedagogical model based) integrated e-learning. The students also created high-quality projects using the computational design method learned in the subject.The pedagogical comparison was conducted between one integrated e-learning based subject (20 students, 5 project groups) and two traditional subjects (114 students, 25 project groups). The findings showed that the students employed in the integrated e-learning based subject demonstrated better capabilities in selecting the target fabrics, previewing the concept design, evaluating the prototype in product development by using a scientific quantitative method, and similar capabilities and attitudes relating to the teamwork experience in product development project compared with the students from the other two traditional subjects.In summary, the pedagogical effects of the integrated e-learning strategy have been investigated systematically with the development of the pedagogical framework, development of the pedagogical model and the pedagogical comparison study between the integrated e-learning and traditional subjects. The integrated e-learning strategy was found to have significant impacts on the students' learning cycles, learning environment and learning outcomes. By using the integrated e-learning strategy, the textiles and clothing university students obtained a deeper understanding of holistic knowledge, and a higher level of skills and application ability in the clothing thermal functional design learning process.

The study aimed at understanding the perceptions of older people among social work students in Hong Kong through examining the antecedent variables of attitudes toward older people and the correlates in the attitude-behavioral intention relationship. By applying an integrated conceptual model based on the ecological-cognitive-social-psychological perspective, six constructs intrinsic to the hypothetical integrative model were examined. They included personal factors, environmental factors, demographic factors, attitudes toward older people, attitudes toward working with older people and intention to work with older people. Besides investigating the predictor-criterion relationships among these six constructs, this study also examined mediating and moderating mechanisms in the conceptual model. This study adopted a cross-sectional design involving two stages. In Stage 1, two new measurements were developed whilst another two Western measurements were translated from English into Chinese. Validity and reliability tests demonstrated that these four measurements possessed adequate psychometric properties.Stage 2 was the main study surveying 569 full-time undergraduate social work students in six local universities. Several significant observations were highlighted. First, knowledge about aging and older people, favorability of experience of contact with older people and personal psychosocial qualities were identified as the three most significant predictors of attitudes toward older people. Second, personal psychosocial qualities, credit-bearing gerontology-related course taken and favorability of experience of contact with older people were identified as the three most significant predictors of attitudes toward working with older people. Third, personal psychosocial qualities was found as a significant predictor of attitudes toward older people and attitudes toward working with older people, respectively. It was regarded as a protective factor of negative attitudes toward older people and ageism. Fourth, the mediating effects of attitudes toward older people, either in complete or partial manner, on the influences of some of the personal and environmental variables on attitudes toward working with older people were confirmed. Fifth, as regards the two attitudinal variables, attitudes toward working with older people but not attitudes toward older people had strong and significant predictive power on intention to work with older people. This finding also gave support for the mediating role of attitudes toward working with older people in the relationship between attitudes toward older people and intention to work with older people. This study has significant contributions. Theoretically, the hypothetical integrative model provides a comprehensive perspective for examining the perceptions of older people among undergraduate social work students at and across different levels of ecosystems and perspectives in Chinese culture. The findings also enrich theory building through the inclusion of the two attitudinal variables and past behavior in the attitude-behavioral intention relation. Educationally, the findings highlight the important of providing adequate gerontology-related knowledge, offering more opportunities for direct exposure to older people and enhancing development of personal psychosocial qualities for building aging-competency through social work education. Practically, the study provides insight on policy directions and ageism-free practices. With the development of the two validated indigenous measurements and the advancement in methodology, the present study as a pioneer of its kind in Hong Kong provides cornerstone for future research.